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20212025
most citedTowards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach

1 citations · 1 across the 7 of their papers we have counts for

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7 papers

cs.LG2025

Diversified Flow Matching with Translation Identifiability

Sagar Shrestha, Xiao Fu

Diversified distribution matching (DDM) finds a unified translation function mapping a diverse collection of conditional source distributions to their target counterparts. DDM was…

eess.SP2025

Domain-Factored Untrained Deep Prior for Spectrum Cartography

Subash Timilsina, Sagar Shrestha, Lei Cheng +1

Spectrum cartography (SC) focuses on estimating the radio power propagation map of multiple emitters across space and frequency using limited sensor measurements. Recent advances i…

cs.LG2024

Content-Style Learning from Unaligned Domains: Identifiability under Unknown Latent Dimensions

Sagar Shrestha, Xiao Fu

Understanding identifiability of latent content and style variables from unaligned multi-domain data is essential for tasks such as domain translation and data generation. Existing…

cs.LG2024

Identifiable Shared Component Analysis of Unpaired Multimodal Mixtures

Subash Timilsina, Sagar Shrestha, Xiao Fu

A core task in multi-modal learning is to integrate information from multiple feature spaces (e.g., text and audio), offering modality-invariant essential representations of data.…

cs.LG2024★ 1 cited

Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach

Sagar Shrestha, Xiao Fu

Unsupervised domain translation (UDT) aims to find functions that convert samples from one domain (e.g., sketches) to another domain (e.g., photos) without changing the high-level…

eess.SP2023

Quantized Radio Map Estimation Using Tensor and Deep Generative Models

Subash Timilsina, Sagar Shrestha, Xiao Fu

Spectrum cartography (SC), also known as radio map estimation (RME), aims at crafting multi-domain (e.g., frequency and space) radio power propagation maps from limited sensor meas…

cs.LG2021

Communication-Efficient Federated Linear and Deep Generalized Canonical Correlation Analysis

Sagar Shrestha, Xiao Fu

Classic and deep generalized canonical correlation analysis (GCCA) algorithms seek low-dimensional common representations of data entities from multiple ``views'' (e.g., audio and…